Title
Wearable-Measured Sleep and Resting Heart Rate Variability as an Outcome of and Predictor for Subjective Stress Measures: A Multiple N-of-1 Observational Study
Author
de Vries, H.J.
Pennings, H.J.M.
van der Schans, C.P.
Sanderman, R.
Oldenhuis, H.K.E.
Kamphuis, W.
Publication year
2023
Abstract
The effects of stress may be alleviated when its impact or a decreased stress-resilience are detected early. This study explores whether wearable-measured sleep and resting HRV in police officers can be predicted by stress-related Ecological Momentary Assessment (EMA) measures in preceding days and predict stress-related EMA outcomes in subsequent days. Eight police officers used an Oura ring to collect daily Total Sleep Time (TST) and resting Heart Rate Variability (HRV) and an EMA app for measuring demands, stress, mental exhaustion, and vigor during 15-55 weeks. Vector Autoregression (VAR) models were created and complemented by Granger causation tests and Impulse Response Function visualizations. Demands negatively predicted TST and HRV in one participant. TST negatively predicted demands, stress, and mental exhaustion in two, three, and five participants, respectively, and positively predicted vigor in five participants. HRV negatively predicted demands in two participants, and stress and mental exhaustion in one participant. Changes in HRV lasted longer than those in TST. Bidirectional associations of TST and resting HRV with stress-related outcomes were observed at a weak-to-moderate strength, but not consistently across participants. TST and resting HRV are more consistent predictors of stress-resilience in upcoming days than indicators of stress-related measures in prior days. (C) 2022 by the authors.
Subject
Police
Stress
Ecology
Heart
Impulse response
Law enforcement
Regression analysis
Sleep research
Wearable technology
Demand stress
Ecological momentary assessment
Heart rate variability
Police officers
Resilience
Resting heart rate
Sleep
Sleep time
Time-series analysis
Wearables
Time series analysis
Electronic device
Physiology
Computers
Heart Rate
Humans
Sleep Duration
Wearable Electronic Devices
To reference this document use:
http://resolver.tudelft.nl/uuid:176fb3a4-60bf-4c07-b2f2-1b56f792d6a8
DOI
https://doi.org/10.3390/s23010332
TNO identifier
981441
ISSN
1424-8220
Source
Sensors, 23 (23)
Document type
article